An approach to case-based system for conceptual ship design assistant

An approach to case-based system for conceptual ship design assistant

Dongkon Lee* , Kyung-Ho Lee

Shipbuilding System Department, Korea Research Institute of Ships and Ocean Engineering (KRISO), P.O.Box 101, Yusung-Gu, Taejeon, 305-600,South Korea

Abstract

Designers heavily depend on their experience and existing ship data, when designing a ship. In preliminary design stage especially,decision making based on the designer’s expertise and heuristic knowledge are very important factors to design process because availableinformation is limited, and cannot be fully supported by formal design procedure and design sheet. To support these conceptual designenvironment, the designer’s experience and heuristic knowledge are transformed into readable formats which can be operated on computersystems. The existing ship data are very useful and important in conceptual design. To use this data efficiently, it requires basically databaseof the existing ships and make practical application of it. In this article, intelligent system that can be a support to the conceptual design stagebased on knowledge engineering was developed. Major design factors and parameters of the existing ship data were stored case base asdesign cases and the case base was connected with database for information exchange among them [Brown, A., Watson, I., & Filer, N.(1995). Separating the cases from the data: towards more flexible case-based reasoning.Proc. of International Conference on Case-BasedReasoning 95(ICCBR-95), Sesimbra in Portugal]. To extract a good and suitable design case for a new ship design from case base, learningalgorithm was adapted. The obtained knowledge from designers was used to compensate for the differences between the design case and anew design. The developed interactive intelligent conceptual design system (BASCON-IV) can be applied to commercial ships and bulkcarriers.q 1999 Elsevier Science Ltd. All rights reserved.

Keywords:Ship design; Case-based system; Knowledge-based system; Conceptual design system

Conceptually, it is evident from any perspective that as adesign process progresses and decisions are made, the free-dom to make changes as one proceeds is reduced and theknowledge about the object of design increased (Mistreeet al., 1990). Conceptual design of a ship is a stage inwhich major specifications are determined according tothe owner’s requirements. At this stage, it is inevitablethat it heavily depends on the experts’ experiences anddesign cases of existing ships because available infor-mation is limited and the degree of design freedom is veryhigh.

In general, the second attempt to solve problems is easierthan the first one because of past experiences (Bhangal,1996). Therefore, one is more intelligent the second timebecause one remembers the past errors and tries to avoidthem. In this sense, the existing ship data is used as designreference by ship designers. This concept or methodology isa developed case-based reasoning in computer science andartificial intelligence. Case-based reasoning technique used

to overcome the defect of rule-based approach is verysimilar to the concept of human reasoning (Liang, 1993).In order to find a solution, a man seeks his solutions fromsimilar past cases and modifies them to fit a given problem.Case-based reasoning does not require an explicit domainmodel and hence, the implementation is reduced to identify-ing significant features that describe a case. In addition, byapplying database techniques largely, volumes of informa-tion can be managed, and case-based reasoning systems canbe learnt by acquiring new knowledge as cases make main-tenance easier (Watson).

In this article, an intelligent system for conceptual shipdesign assistant based on case-based reasoning technologyis presented. Major design factors and parameters of theexisting ship data are stored case base as design cases andthe case base is connected with database for informationexchange among them. To extract a good and suitabledesign case for a new ship design from case base, learningalgorithm is adapted. The obtained knowledge fromdesigners is used to compensate for the differences betweendesign case and a new design. The developed interactiveintelligent conceptual design system (BASCON-IV) canbe applied to commercial ships and bulk carriers.

Expert Systems with Applications 16 (1999) 97–104PERGAMON

Expert Systemswith Applications

ESWA 794

0957-4174/99/$ - see front matterq 1999 Elsevier Science Ltd. All rights reserved.PII: S0957-4174(98)00064-5

* Corresponding author. Tel.:1 82-42-868-7222; Fax:1 82-42-868-7229; e-mail: [email protected]

2. Ship design environment

In the shipbuilding industry, ships are built in smallnumbers with many different designs depending on theowner’s requirements. To secure orders from owners,designers have to design efficient, high performance shipswithin a fixed time period (Lee and Lee, 1996). In shipdesigning, data of existing ships are used largely becauseavailable data are limited and the freedom of design is veryhigh. During the conceptual stages of design, for example,the principal particulars and major performance of the shipare estimated by comparison with ships of a similar type orfrom coefficients derived from existing ships (Han and Lee,1994). Therefore, designers should closely study, analyze,and structure the design data from similar ships that havebeen built in the recent past. These data can be implementedas a database and utilized to improve the quality and shortenthe time of designing.

Ship designers select properly existing ships from data-base based on their experience and characteristics of ships,such as ship type, size, speed and so on. Some referenceships and/or a mother ship is chosen based on the designer’spreference and experience only after sorting out similarships from the existing ships’ database. The selection ofgood reference ships is essential for deriving a good initialdesign, and the quality of the initial design directly affectsthe efficiency and quality of the whole conceptual designprocess. Design experts relying on their experience andengineering knowledge of ship design and structuralmechanics have so far done the selection of referenceships. Therefore the selected reference ship could be chan-ged in accordance with the characteristics of designersunder same situations. The reference ships are used forderiving the initial design of a new ship and then this initialdesign is kept modified and repaired until the design reachesa level of satisfactory quality (Andrews, 1981). The ship ispractically designed based on past experience and referenceship data, assuming that reference ships represented opti-mum designs and that small changes would not be econom-ically unsatisfactory, though such changes could adverselyaffect the performance of the ships. If we consider that shipdesigning is performed mainly on the basis of past similarship design cases, case-based reasoning concept is the idealone to adopt in ship designing process, especially in concep-tual ship designing.

3. Case-based approach for ship design

Case-based reasoning systems reason from experience;they solve new problems by retrieving relevant prior casesand adapting them to fit new situations (Jasbir, 1996; Reis-beck, 1989 and Kolodner, 1993). Case-based reasoningsystems process new situations by retrieving a relevantprior case from memory, comparing that case to the newsituation to determine important similarities and differences,

and applying pertinent information from the old case to thenew situation (Lorenzo, 1996).

Case-based reasoning is a technology used to develop aknowledge-based system known as the case-based system.The basic idea is, given the description of a new problem,retrieving from a case base a similar problem and the solu-tion of this case is adapted to a new problem. A case-basedsystem has two main components, a case base and a problemsolver. The case base contains the description of the solvedand unsolved problems. The problem solver has twomodules, the retriever and the reasoner.

Given the description of the problem, the set of featuresthat define it, the retriever has the function of searching andretrieving a similar case from the case base. One way forsearching a similar case is by using a similarity function.This function determines the measure of similarity betweenthe new problem and each stored case. Whereas more infor-mation takes into account this function the measure will bebetter, among them are taken into account those featuresthat have different weight and the comparison function foreach feature.

As mentioned earlier, case-based reasoning is a reason-able and reliable approach in the domain of ship designbecause it can not only offer design candidates by indexingand similarity assessment, but can also compensate for theinsufficiency of cases by adaptation of similar cases.

3.1. Case base

The major factor used to select a reference ship is extractedand stored to the case base. Stored items are ship name, shiptype, ship size, design speed, and cargo handling equipment,and so on. This article represents a case as five components:title, description, question, answer, and action.

Title:The case title is a one-line phrase that uniquely identifies thecase. For the conceptual design, it means the name of ship,for example,Queen Mary, and so on.Description:The description is a critical paragraph of text that forms thebasis for the first search. It represents the key feature of acase. We regard the description as ship type such as bulkcarrier, tanker, and container.Question and answer:Question is used for case description to confirm variousaspects of the case. Through the questions and theiranswers, case-based reasoning system finds the most similarcase by way of matching algorithm, particularly the nearestneighbor algorithm. Here, the owner’s requirements likedead weight, cargo volume, speed, are described. In addi-tion, cargo type, existence of crane and builder are alsopresented. All items have their own weights according totheir importance or influence on the case.Action:Action corresponds to a solution of the problem. In this

D. Lee, K.-H. Lee / Expert Systems with Applications 16 (1999) 97–10498

article, ship identification number is described as action, andthe values of design parameters are searched in existing shipdatabase according to the number.

Fig. 1 shows an implemented case for the conceptualdesign of a bulk carrier.

3.2. Case indexing

The conceptual ship design process begins with selectingreference ships of the same type with similar sizes and speedsthat were designed earlier. These reference ships are used forderiving an initial design of a new ship and then the initialdesign is kept modified and repaired until the design resultreaches a level of satisfactory quality. The selection of goodreference ships is essential for deriving a good initial design,and the quality of the initial design affects the efficiency andquality of the whole conceptual design process.

We developed a memory-based learning method that can

build an effective indexing scheme for retrieving good refer-ence cases from a case base of previous ship designs (Lee etal., 1997). An indexing technique plays an important role ina case-based reasoning system as it helps the system find agroup of suitable candidates to deal with. Memory-basedlearning is the technique by which the acceptable rangesof the relevant parameters in designing of the existingcases are trained to memorize through learning. Fig. 2shows how memory-based learning can be used for select-ing the reference ship, given a new ship of specified speedand dead weight (DWT) requirement. In Fig. 2, ships of pastdesign are designated by thex’s and each of them isenclosed by a boundary, which represents the range withinwhich the ship is worth referencing. A new ship of specifiedspeed and DWT is shown in Fig. 2 as a point indicated by anarrow. For a new shipq1, x1 becomes a reference ship. Forq2, bothx2 andx3 are worth referencing, while the one closerto q2 under a certain similarity measure becomes the mothership. For shipq3, there is no reference ship available becausenone of the previous ships is similar to this. Note thatx2 isworth referencing to a wider range than any others, andx4

seems exceptional and thus it is never referenced for a newship design. Note also that the range of reference forx4 issensitive to speed, and in general the boundaries for theships are not necessarily in regular or symmetric shapes.The two important tasks of our learning algorithm are todetermine the range of reference for each ship and toprovide a way to measure the degree of similarity betweenthe two given ships. As shown in Fig. 2, if there are a lot ofpast-designed ships, several similar ships can be referencedas design candidates for a given design ship. Of course,there can be other design parameters to be considered inselecting reference ships. This case brings about a compli-cated indexing process.

D. Lee, K.-H. Lee / Expert Systems with Applications 16 (1999) 97–104 99

Fig. 2. An MBL approach to reference ship selection.

Fig. 1. An example of implemented case for conceptual ship design.

3.3. Case retrieval

The priorities of the design candidates obtained by index-ing technique are determined according to the similarityassessment derived through the matching algorithm. Match-ing algorithm to be presented are of three kinds: numeric,heuristic, and mixed. Numeric procedures depend on anumeric evaluation function that computes a match scorebased on relative importance of features and the degree ofmatch for each case. We introduced a nearest neighbor algo-rithm based on numeric procedure. The nearest neighboralgorithm involves the assessment of similarity betweenstored cases and a new input case, based on matching aweighted sum of features. Computing the degree of matchcan be a fairly straightforward process that uses a numericalevaluation function. Every feature in the input case is

matched to its corresponding feature in the stored or oldcase, the degree of match for each pair is computed, andbased on the importance assigned to each dimension, anaggregate match score is computed.

The types of features are divided into four kinds: Yes/No,Text, Numeric, and List. Yes or No type is simply a binarychoice, and successive trigram character matching is donefor text typed feature. List type is a straightforward type inmatching the feature, so only the matching concept ofnumeric type of feature, which is mainly manipulated indesign problem is described in this article. The degree ofmatch of numeric feature is determined by the followingprimary factors: maximum allowable value, minimumallowable value, match deviation, minimum error range,and so on. Fig. 3 shows the calculation of degree of matchabout ship speed, one of the matching features. In this case,the minimum allowable value is 0, the maximum allowablespeed 25 knots, the deviation 4.5, and the weight for exactmatch 10, and for mismatch2 2, the speed of stored case is15 knots, and given speed of design ship is 14 knots. Thedegree of match is 7 for a given speed. Total similaritymetrics is represented as the summation of degree ofmatch for every feature.

Generally the total similarity metrics is calculated asfollows:

Similarity metrics�Xpi�1

Si 2Xqj�1

Mj 2Xr

k�1

Ak

whereS is the weighted value for matched feature;M theweighted value for mismatched feature;A the weightedvalue for not-existed feature;p the number. of matched


Fig. 3. Calculation of similarity metrics by nearest neighbor algorithm.

Fig. 4. Adaptation by knowledge-based approach.

feature; q the number of mismatched feature, andr thenumber of not-existed feature.

This similarity metrics is used through the normalizationprocess. With the case, which is the nearest one, the detailedinformation extracted from the database is referred to indesign process as mother ship data.

3.4. Case adaptation

The selected case still does not, in general, satisfy allthe requirements of the vessel to construct, and requiresome adaptation of the candidate. The knowledge-basedapproach or genetic algorithm is employed in the adap-tation (Maher, 1996). In this article, we adopt knowledge-based approach for some adaptation process. Knowledge-based reasoning accomplishes the adaptations for principalparticulars and compartment division. Fig. 4 shows anexample of knowledge-based adaptation process for thedetermination of principal dimensions. For other designmodules, we substituted conceptual design program basedon empirical formulas for adaptation process. The concep-tual design program named BASCON-III, which was devel-oped in Computerized Ship Design and Product System(CSDP) project sponsored by the Ministry of Science andTechnology of Korea performs its design on the basis ofmother ship data (Lee and Lee, 1994). The selection ofmother ship data is replaced by case-based reasoningtechnique, especially indexing and retrieving, and thedesign processes such as principal particulars’ deter-mination, compartment division, weight estimation, andvolume calculation, are regarded as adaptation. As theseengineering modules generate the design values of newship based on mother ship data, which is selected fromdesign candidates by similarity assessment. The followingis an example of the knowledge for adaptation of principalparticulars.

Rule 1:

If (Yes (adapt_B))(Yes (adapt_LBP))(Yes (adapt_D))(Yes (adapt_T))(Yes (adapt_CB))

Hypo adapt_PD

Rule 2:

If (, . (new_ship.size) (‘‘PANAMAX’’))(. � (new_ship.DWT) (70000))

Hypo adapt_BThen (Assign (19.9711.925*new_ship.DWT-0.02325*POW(new_ship.DWT,2))(new_ship.B_E))(Assign(new_ship.B_E*(11(new_ship.DWT-mother_ship.DWT)/mother_ship.DWT))(new_ship.B))

Rule 3:

If (� (new_ship.size)(‘‘PANAMAX’’))Hypo adapt_BThen (Assign (32.2)(new_ship.B))

Rule 4:

If (Yes calc_lbp)(. � new_ship.L_over_B 5.5)(, � new_ship.L_over_B 7.0)

Hypo adapt_LBPThen (Assign (6.0*new_ship.B)(new_ship.LBP_E))

(Assign (new_ship.LBP_E*(11 (new_ship.DWT-mother_ship.DWT)/mother_ship.DWT))(new_ship.LBP_E))

Rule 5:

If (Assign (124.26117.35*new_ship.DWT-0.641*POW(new_ship.DWT,2)1


Fig. 5. Configuration of interactive conceptual design, BASCON-III.

0.01024*POW(new_ship.DWT,3)) (new_ship.LBP))Hypo calc_lbp

4. An intelligent system for conceptual design assistant

The conceptual design support system we studied in thisarticle is the result of integration of the case-based reasoningsystem, knowledge-based system and an interactive concep-tual design system named BASCON-III.

4.1. Interactive conceptual design system: BASCON-III

As mentioned earlier, a ship designer must perform theconceptual design based on his/her creativity and designexperiences. A computer system supporting the conceptualdesign is required, which has not only a design model forcreative works but also a flexible model to adapt to thechanging circumstances. Developments in the conceptualship design have changed from the batch version systemBASCON-I (Lee and Lee, 1990) to the user oriented inter-active system BASCON-II (Lee and Lee, 1992). Howeverthese systems have been developed only to integratemodules, but these systems must also have flexibility inorder that each module can be executed independently tomeet specific needs. Based on this concept the controlmodule is implemented by using UNIX shell programming.This module controls the job process at the top level. Itperforms the functions of execution of arbitrary modules,storing of job history and back-tracking. By integrating thecontrol module, nine design modules and a graphical userinterface, an adaptable user oriented conceptual ship designsystem, BASCON-III, was developed (Lee and Lee, 1994).Fig. 5 shows the configuration of the BASCON-III. Alldesign modules are separated. Therefore the user canexecute each design module independently. Addition tothe separation of modules, the functions of execution ofarbitrary modules and back-tracking are possible.

4.2. Interactive intelligent conceptual design system:BASCON-IV

We adopt CasePoint (Inference Corporation, 1996) as atool of integration of engineering modules with a case basemodule. In the process of integration, the ApplicationProgramming Interface (API) program based on remote


Fig. 6. Configuration of the intelligent conceptual design assistant system,BASCON-IV.

Fig. 7. Design examples of the interactive intelligent conceptual design system, BASCON-IV.

procedure control (RPC) protocol concepts was utilized.That is, API program is constructed by data exchange func-tions between application RPC client and CasePoint RPCserver, and composed of three parts: initialization, callback,and update. A part of pseudo code of API for initialization isas follows:

Begin

initiate a RPC session with CasePointopen a case base set description (using application data)searchset answer to questions (using application data)search

End

The roles of callback and update are such that the evalua-tion of similarity assessment is performed according to theorder passed from the application program, and a solutionreturn is made to the application program. The pseudo codefor callback and update is as follows.

Begin

for each questionbegin

get answer to questionset application data to answer value

endget title of highest scoring case (if not known via call-back)get text associated with highest scoring caseset application data to case text

End

Fig. 6 shows the configuration of the interactive intel-ligent conceptual design system, BASCON-IV in whichcase base, knowledge base, conceptual design system,and database are integrated by API module. Fig. 7shows the design examples of the interactive intelligentconceptual design system, BASCON-IV, where thetrained cases by MBL are visualized and the design candi-dates are presented in the middle of conceptual designprocess.

4.3. Application example to ship design

An exact solution, in general, was not found in the engi-neering design unlike mathematical problems. As we do nothave the criteria to evaluate all parameters of design resultand these parameters have trade-off relationship, evaluationfor designed ship usually depend on designer’s expertise orexisting ship data. To evaluate performance of the devel-oped interactive intelligent conceptual design system(BASCON-IV) in this article, its result is compared to anexisting ship data and result of the adaptable user orientedconceptual ship design system (BASCON-III).

In BASCON-III, the data of similar ships are sorted fromthe database of ship particulars according to the ship type,deadweight, speed, and so on. Among the sorted ship data,user selects a ship as a mother ship. In BASCON-IV, by theway, the similarity metrics is used to select a mother ship(design case). The same ship is given as mother ship forimpartial measure. Input data for BASCON-IV andBASCON-III is also given same value such as 155 000deadweight for capacity and 14.83 knot for speed. Evalua-tion result for principal particulars is summarized in Table1. Mother ship in Table 1 is used basis ship data forBASCON-III and design case for BASCON-IV, respec-tively. Result of BASCON-IV is more acceptable incomparison with BASCON-III. We know that the knowl-edge-based adaptation in BASCON-IV give better resultsthan empirical formula in BASCON-III.

5. Conclusion

As mentioned earlier, in a conceptual design availableinformation is limited, and makes it attractive to rely onthe design cases of existing ships to design a ship satisfyingthe requirements by suitable modification of them. Case-based reasoning technique is very adaptable in such aconceptual ship design stage. In this article, we focusedon the use of case-based reasoning for selecting referenceships in conceptual design stage. We developed a memorybased learning method that can build an effective indexingscheme for retrieving good reference cases from a case baseof previous ship designs as design candidates. Of the design


Table 1Evaluation result of the interactive intelligent conceptual design system

Existing ship Mother ship BASCON-III BASCON-IV

Deadweight (ton) 155 000 140 000 155 000 155 000Speed (knots) 14.83 14.2 14.83 14.83LBP (m) 281 259 277.3 280Breadth (m) 46 43 44.2 46Depth (m) 23.2 23.8 22.8 23.2Draft (m) 16 16.5 17.7 16Cb 0.83 0.836 0.835 0.832

candidates obtained by indexing process, their priorities aredetermined according to similarity assessment derivedthrough the nearest neighbor matching algorithm. Comput-ing the degree of match by using the algorithm is straight-forward and easy. Indexing and retrieving processes aresuitable tools to assist a designer in conceptual designprocess. And as the interactive intelligent conceptual designsystem is integrated with case base, database, and interac-tive conceptual design program by API module, it is possi-ble to support the process of design intelligently. As a resultof this work, a reliable design support system is now avail-able which greatly helps ship designers perform the concep-tual design using existing mother ship data.

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An approach to case-based system for conceptual ship design assistant